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Home / programming language / Online Java Projects / SVM-based Web Content Mining with Leaf Classification Unit from DOM-tree
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SVM-based Web Content Mining with Leaf Classification Unit from DOM-tree

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SKU: PROJ8000 Categories: 2018-2019 Projects, Datamining Projects, Online Java Projects Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Matlab Project, PHP Project, Students Projects
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SVM-based Web Content Mining with Leaf Classification Unit from DOM-tree

Abstract-In order to analyze a news article dataset, we first extract important information such as title, date, and paragraph of the body. At the same time, we remove unnecessary information such as image, caption, footer, advertisement, navigation and recommended news. The problem is that the formats of news articles are changing according to time and also they vary according to news source and even section of it. So, it is important for a model to generalize when predicting unseen formats of news articles. We confirmed that a machine learning based model is better to predict new data than a rule-based model by some experiments. Also, we suggest that noise information in the body possibly can be removed because we define a classification unit as a leaf node itself. On the other hand, general machine learning based models cannot remove noise information. Since they consider the classification unit as an intermediate node which consists of the set of leaf nodes, they cannot classify a leaf node itself.< final year projects >

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